LLM Content Access & Usage Policy
Last Updated: 2025-07-03
This document outlines the rules and guidelines regarding access to and use of LLM-generated content and services provided by wizee.me. Our platform offers free access to large language models (LLMs) through an interface monetized by advertisements. This policy is designed to protect our infrastructure, monetization model, and intellectual property, while also encouraging fair and ethical usage.
⚠️ By accessing or interacting with our LLMs, you agree to the terms outlined in this policy.
1. Who May Access Our Services
We allow access to our public LLM services under the following conditions:
- Humans using our interface through a browser with ads enabled.
- Interactive bots from verified services (e.g.,
openai.com
,anthropic.com
,huggingface.co
).
All other automated agents or crawlers must request prior written authorization before accessing or interacting with our models.
2. Prohibited Activities
- Automated scraping or crawling of prompt/output pairs.
- Using our content for training or fine-tuning LLMs without explicit license.
- Rehosting or mirroring our LLM interface or content outside of our site.
- Bypassing advertisement layers or monetization mechanisms.
3. Attribution & Reuse Conditions
You may share generated content provided that:
- Proper attribution to wizee.me is included.
- Any sponsored content (ads, branded results) is preserved.
- You do not monetize or repackage the outputs without a commercial agreement.
4. Technical Enforcement
We use the following mechanisms to communicate and enforce our preferences:
/robots.txt
– for search engines and LLM crawlers./llm.txt
– our public machine-readable LLM policy.- Firewall and rate-limiting for unknown or abusive agents.
5. Contact & Licensing
To inquire about licensing data or requesting special access for research or commercial use, please contact us:
- Email: info@leafsrls.com
- License Requests: /license
- Full Terms of Use: /terms
6. Violations
Unauthorized use of our content, services, or underlying data may result in:
- IP bans or legal takedowns.
- Reporting to upstream platforms or registrars.
- Litigation under applicable copyright, computer access, or contract laws.